org.nd4j.linalg.api.ops.impl.transforms.custom.BatchToSpaceND Maven / Gradle / Ivy
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package org.nd4j.linalg.api.ops.impl.transforms.custom;
import lombok.val;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.linalg.api.buffer.DataType;
import org.nd4j.linalg.api.ops.DynamicCustomOp;
import java.util.Arrays;
import java.util.Collections;
import java.util.List;
public class BatchToSpaceND extends DynamicCustomOp {
private int[] blocks;
private int[][] crops;
public BatchToSpaceND() {
}
public BatchToSpaceND(SameDiff sameDiff, SDVariable[] args, int[] blocks, int[][] crops, boolean inPlace) {
super(null, sameDiff, args, inPlace);
this.blocks = blocks;
this.crops = crops;
for (val b : blocks)
addIArgument(b);
for (int e = 0; e < crops.length; e++)
addIArgument(crops[e][0], crops[e][1]);
}
@Override
public String opName() {
return "batch_to_space_nd";
}
@Override
public String onnxName() {
return "batch_to_space_nd";
}
@Override
public String tensorflowName() {
return "BatchToSpaceND";
}
@Override
public List doDiff(List i_v) {
// Inverse of batch to space is space to batch with same blocks and padding as crops
SDVariable gradient = sameDiff.setupFunction(i_v.get(0));
return Arrays.asList(sameDiff.cnn().spaceToBatch(gradient, blocks, crops[0], crops[1]));
}
@Override
public List calculateOutputDataTypes(List dataTypes){
return Collections.singletonList(dataTypes.get(0));
}
}